The DOI matches its Crossref record; 3 of the 3 references it cites were found in a registry or an index.
Converting a breast cancer microarray signature into a high-throughput diagnostic test
Open accessAbstract
BACKGROUND: A 70-gene tumor expression profile was established as a powerful predictor of disease outcome in young breast cancer patients. This profile, however, was generated on microarrays containing 25,000 60-mer oligonucleotides that are not designed for processing of many samples on a routine basis. RESULTS: To facilitate its use in a diagnostic setting, the 70-gene prognosis profile was translated into a customized microarray (MammaPrint) containing a reduced set of 1,900 probes suitable for high throughput processing. RNA of 162 patient samples from two previous studies was subjected to hybridization to this custom array to validate the prognostic value. Classification results obtained from the original analysis were then compared to those generated using the algorithms based on the custom microarray and showed an extremely high correlation of prognosis prediction between the original data and those generated using the custom mini-array (p < 0.0001). CONCLUSION: In this report we demonstrate for the first time that microarray technology can be used as a reliable diagnostic tool. The data clearly demonstrate the reproducibility and robustness of the small custom-made microarray. The array is therefore an excellent tool to predict outcome of disease in breast cancer patients.
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Gene expression profiling predicts clinical outcome of breast cancer
van 't Veer, L. J., Dai, H., van de Vijver, M. J., He, Y. D., Hart, A. A. M., Mao, M., Peterse, H. L., van der Kooy, K., Marton, M. J., Witteveen, A. T., et al. (2002) · Nature · doi:10.1038/415530a · Cited by 9,536
Self-citationKhan, J., Wei, J. S., Ringnér, M., Saal, L. H., Ladanyi, M., Westermann, F., Berthold, F., Schwab, M., Antonescu, C. R., Peterson, C., et al. (2001) · Nature Medicine · doi:10.1038/89044 · Cited by 2,644
Ayers, M., Symmans, W. F., Stec, J., Damokosh, A. I., Clark, E., Hess, K., Lecocke, M., Metivier, J., Booser, D., Ibrahim, N., et al. (2004) · Journal of Clinical Oncology · doi:10.1200/jco.2004.05.166 · Cited by 566
Cited by
Nanda, R., Liu, M. C., Yau, C., Shatsky, R., Pusztai, L., Wallace, A., Chien, A. J., Forero-Torres, A., Ellis, E., Han, H., et al. (2020) · JAMA Oncology · doi:10.1001/jamaoncol.2019.6650 · Cited by 710
Statnikov, A., Wang, L., & Aliferis, C. F. (2008) · BMC Bioinformatics · doi:10.1186/1471-2105-9-319 · Cited by 686
Adaptive Randomization of Veliparib–Carboplatin Treatment in Breast Cancer
Rugo, H. S., Olopade, O. I., DeMichele, A., Yau, C., van ’t Veer, L. J., Buxton, M. B., Hogarth, M., Hylton, N. M., Paoloni, M., Perlmutter, J., et al. (2016) · New England Journal of Medicine · doi:10.1056/nejmoa1513749 · Cited by 554
Self-citationTumor Microenvironment Complexity: Emerging Roles in Cancer Therapy
Swartz, M. A., Iida, N., Roberts, E. W., Sangaletti, S., Wong, M. H., Yull, F. E., Coussens, L. M., & DeClerck, Y. A. (2012) · Cancer Research · doi:10.1158/0008-5472.can-12-0122 · Cited by 542
On behalf of the TRANSBIG consortium, Mook, S., Schmidt, M. K., Viale, G., Pruneri, G., Eekhout, I., Floore, A., Glas, A. M., Bogaerts, J., Cardoso, F., et al. (2009) · Breast Cancer Research and Treatment · doi:10.1007/s10549-008-0130-2 · Cited by 299
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Metadata
- Authors
- Glas, A. M., Floore, A., Delahaye, L. J., Witteveen, A. T., Pover, R. C., Bakx, N., Lahti-Domenici, J. S., Bruinsma, T. J., Warmoes, M. O., Bernards, R., Wessels, L. F., & Van 't Veer, L. J.
- Venue
- BMC Genomics
- Published
- 2006-10-30
- Volume
- 7
- Issue
- 1
- Pages
- 278-278
- ISSN
- 1471-2164 (ISSN-L)
- OpenAlex
- W2154976095
- Cited by
- 494
- References
- 3
- FWCI
- 14.99
- Type
- journal article
- Language
- en
- Open access
- gold
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- Glas, A. M., Floore, A., Delahaye, L. J., Witteveen, A. T., Pover, R. C., Bakx, N., Lahti-Domenici, J. S., Bruinsma, T. J., Warmoes, M. O., Bernards, R., Wessels, L. F., & Van 't Veer, L. J. (2006). Converting a breast cancer microarray signature into a high-throughput diagnostic test. BMC Genomics. https://doi.org/10.1186/1471-2164-7-278
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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
